Role & responsibilities

We are seeking a QA Lead with 10+ years of strong expertise in Automation, Performance Engineering, and Observability to ensure platform reliability across a distributed microservices architecture..

Extensive experience in AI and AI implementation
Hands-on experience with AI Agents and AI-driven workflows

The QA Lead will work closely with Engineering, DevOps, and SRE teams to ensure high-quality releases and improved system reliability.

Key Responsibilities:
Test Automation Leadership.
Design and maintain automation frameworks for API, integration, and end-to-end testing.
Develop system-level regression suites covering event-driven workflows, data pipelines, and asynchronous processing
Build regression coverage for cross-service customer workflows.
Integrate automation into CI/CD pipelines.
Drive automation best practices across teams.

Tools:

API Testing: Postman, RestAssured
UI Automation: Selenium, Playwright
Frameworks: PyTest, TestNG
CI/CD: Jenkins, GitHub Actions, GitLab CI

Performance Engineering:

Design and execute load, stress, and endurance testing.
Identify performance bottlenecks in distributed services
Validate system scalability and stability before releases.

Tools:

JMeter
K6

Observability & Production Diagnostics:

Monitor system behaviour using observability platforms.




Investigate production incidents and perform root cause analysis.
Reproduce production defects in lower environments.
Identify testing gaps based on incident patterns.

Tools:

Datadog
Splunk

AI-Enabled Quality Engineering (Nice to Have):

Experience leveraging AI tools to improve testing efficiency and defect detection.

Examples include:

AI-assisted test case generation.
AI-assisted automation development (GitHub Copilot or similar tools)
AI-driven defect clustering and log analysis.
AI-powered anomaly detection from observability data.

Technical Skills:

Programming: Python, Java, JavaScript
Test automation frameworks for API and E2E testing
CI/CD pipelines and DevOps workflows

Preferred Experience:

Containerized environments (Docker, Kubernetes)
Working with SRE / platform teams

Preferred candidate profile

Immediate joiners .

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Perks and advantages

Full Time opportunity

Direct Payroll

WFO.

📌 Qa Automation Lead (Pune)
🏢 Data Wave Technologies India
📍 Pune